alphabeta

alphabeta

class AlphaBetaPlayer(IsolationPlayer):
   
        self.time_left = time_left



    def terminal_test(self, game):
        if self.time_left() < self.TIMER_THRESHOLD:
            raise SearchTimeout()
        return not bool(game.get_legal_moves())

    def max_value(self, game, depth, alpha=float("-inf"), beta=float("inf")):
        """ Return the value for a loss (-1) if the game is over,
        otherwise return the maximum value over all legal child
        nodes.
        """
        if self.time_left() < self.TIMER_THRESHOLD:
            raise SearchTimeout()
        if depth >= self.search_depth:
            return self.score(game, game.active_player)
        depth += 1
        if self.terminal_test(game):
            return -1
        v = float("-inf")
        for m in game.get_legal_moves():
            v = max(v, self.min_value(game.forecast_move(m), depth, alpha, beta))
            if v >= beta:
                return v
            alpha = max(alpha, v)
        return v

    def min_value(self, game, depth, alpha=float("-inf"), beta=float("inf")):
        """ Return the value for a win (+1) if the game is over,
        otherwise return the minimum value over all legal child
        nodes.
        :param game:
        :param depth:
        :return:
        """
        if self.time_left() < self.TIMER_THRESHOLD:
            raise SearchTimeout()
        if depth >= self.search_depth:
            return self.score(game, game.active_player)
        depth += 1
        if self.terminal_test(game):
            return 1
        v = float("inf")
        for m in game.get_legal_moves():
            v = min(v, self.max_value(game.forecast_move(m), depth, alpha, beta))
            if v >= alpha:
                return v
            beta = max(beta, v)
        return v

    def alphabeta(self, game, depth, alpha=float("-inf"), beta=float("inf")):
       
        if self.time_left() < self.TIMER_THRESHOLD:
            raise SearchTimeout()

        depth = 1
        best_score = alpha
        best_move = None
        for m in game.get_legal_moves():
            v = self.min_value(game.forecast_move(m), depth, alpha, beta)
            if v > best_score:
                best_score = v
                best_move = m
        return best_move